This packages provides C++ header files for developers wishing to create R packages that processes BAM files. ompBAM automates file access, memory management, and handling of multiple threads 'behind the scenes', so developers can focus on creating domain-specific functionality. The included vignette contains detailed documentation of this API, including quick-start instructions to create a new ompBAM-based package, and step-by-step explanation of the functionality behind the example packaged in
インストールする前に、エージェントに与えられる指示の中身を確認できます。
library(ompBAM)
# Create a new package template that compiles with ompBAM
pkg_path <- file.path(tempdir(), "MyPkg")
use_ompBAM(pkg_path)
# Retrieve the path to an example BAM file provided by the package
bam_path <- ompBAM::example_BAM("Unsorted")
Input: A destination directory path for the new package.
Output: A fully configured R package directory structure containing C++ templates and configuration files linked to ompBAM.
ompBAM to handle file access, BGZF decompression, and thread management.pbam_in and pbam1_t APIs).Rsamtools or GenomicAlignments instead.htslib directly as ompBAM is optimized for whole-file sequential reads.Rcpp and a C++ compiler supporting OpenMP (e.g., gcc or clang with OpenMP libraries).use_ompBAM): The directory path where the new package project will be created.devtools::document() on the newly created package to generate the NAMESPACE and export the R wrapper functions.#ifdef _OPENMP directive in C++ code to ensure compatibility with systems that do not have OpenMP installed (such as default macOS configurations).pbam1_t::realize() if you need to store reads in memory across multiple calls of pbam_in::fillReads(), as virtual reads point to temporary buffers.libomp via Homebrew (brew install libomp) and configure compiler flags.pbam1_t objects after calling fillReads() leads to segmentation faults. Fix: Call realize() on the pbam1_t object to copy the data into persistent memory.omp_get_max_threads().まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
The package contains functions for exploratory oligonucleotide array analysis. The dependence on tkWidgets only concerns few convenience functions. 'affy' is fully functional without it.
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This tool uses the label-tree function from HyPhy to annotate a phylogenetic tree. It allows users to select a subset of leaves using either a regular expression or a list of sequence names, and then apply a specified label to these selecte
日本語の概要は準備中です。原文の説明を表示しています。
This package provides a client for the Bioconductor AnnotationHub web resource. The AnnotationHub web resource provides a central location where genomic files (e.g., VCF, bed, wig) and other resources from standard locations (e.g., UCSC, En
日本語の概要は準備中です。原文の説明を表示しています。
apeglm provides Bayesian shrinkage estimators for effect sizes for a variety of GLM models, using approximation of the posterior for individual coefficients.
日本語の概要は準備中です。原文の説明を表示しています。
ASURAT is a software for single-cell data analysis. Using ASURAT, one can simultaneously perform unsupervised clustering and biological interpretation in terms of cell type, disease, biological process, and signaling pathway activity. Inputting a single-cell RNA-seq data and knowledge-based databases, such as Cell Ontology, Gene Ontology, KEGG, etc., ASURAT transforms gene expression tables into original multivariate tables, termed sign-by-sample matrices (SSMs).
日本語の概要は準備中です。原文の説明を表示しています。
AUCell allows to identify cells with active gene sets (e.g. signatures, gene modules...) in single-cell RNA-seq data. AUCell uses the "Area Under the Curve" (AUC) to calculate whether a critical subset of the input gene set is enriched with
日本語の概要は準備中です。原文の説明を表示しています。